I updated my question.
I made phylogenetic trees using RaxML and MrBayes. I am wondering how to merge the bootstrap values and Bayesian posterior probabilities of common branches to show in the tree. For example one node would look like 95, 0.99 . Let me know if you are aware of any program which does this. Thank you.
2 answers
I wouldn't "merge" bootstrap values and posterior probability values -- I usually see both recorded on a tree -- at least I have never seen the values "merged" (not really sure what "merge" means in this context).
Some people choose to record one (usually bootstrap) above the branch and the other (usually posterior probabilities) under the branch. You might also see one value separated by another value (such as BV/PP) across the top of a branch.
You should check if the journal you are submitting to has a data reporting requirement and always make sure you have an explanation in the key or figure caption.
Open the tree in any text editor and make the changes there?
Here's an interesting post on the topic, with some solutions using the ape package in R: http://treethinkers.blogspot.com/2008/10/labeling-trees-posterior-probability.html
In the comments, the developer of Dendropy points out that his Sumtrees script (http://pythonhosted.org/DendroPy/scripts/sumtrees.html) will plot bootstrap values onto a target tree, although I don't think it can handle BOTH bootstrap and posterior probabilities plotted onto the same branch.
This other post on the same blog shows how it could be done in R with symbols, rather than numbers: http://treethinkers.blogspot.com/2008/07/r-tip-indicating-tree-support.html
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So, do you have two separate trees, one generated from each program?
I haven't used MrBayes myself, but I am guessing since you are using ML for RAxML and Bayesian Inference for MrBayes, wouldn't the topology of these two trees look different already? If so, how would it be even possible to put two values to the nodes? Are you doing this only for the common nodes (i.e. nodes that appear both in your ML and Bayesian trees)?